Lead Quantitative Risk Analyst, Advanced Analytics & Credit Modelling

RBC•Toronto, ON

3d•Onsite

About The Position

As part of the Commercial & Wholesale Credit Risk, the Lead Quantitative Risk Analyst, Advanced Analytics & Credit Modelling will work closely with the model development team and credit risk experts to understand drivers of changes in PCL and support the broader team in delivering deeper analysis. You'll combine technical expertise with business acumen to analyze client behavior, evaluate credit performance, and assess Stage 3 PCL / Coverage trends.

Requirements

Undergraduate degree in Mathematics, Statistics, Computer Science, Finance or other quantitative field of study
Strong technical and automation skills such as SQL, Python to manage very large relational databases
Expert in MS Excel and PowerPoint.
Strong analytical and statistical skills, with experience analyzing financial data and supporting model development.
Solid understanding of credit risk and financial processes.
Strong communication skills with the ability to explain analytical findings clearly.

Nice To Haves

Master’s degree in CS, finance, mathematics, statistics, or economics.
Knowledge of other programming languages such as R or SAS.
Prior model development / reporting experiences for IFRS9, stress testing or capital measurement.

Responsibilities

Support the development of Machine Learning, credit scoring, and Stage 3 PCL loss forecasting models to reduce losses and drive revenue.
Extract, clean, validate, and analyze data from multiple sources to quantify borrower behavioral patterns and identify credit loss drivers and trends.
Support the broader team's initiatives, analytics, and ad hoc requests.
Run various monthly and quarterly reporting, drive continuous improvement initiatives in collaboration with the broader team.
Prepare reports and presentations summarizing key findings for review by senior leadership.
Prepare comprehensive documentation, source codes, presentation decks, and model monitoring reports.